Instructions to use hamishivi/fixed-roberta-base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hamishivi/fixed-roberta-base with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="hamishivi/fixed-roberta-base")# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("hamishivi/fixed-roberta-base") model = AutoModel.from_pretrained("hamishivi/fixed-roberta-base") - Notebooks
- Google Colab
- Kaggle
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Check out the documentation for more information.
Fixed-roberta-base
roberta-base but with a resized embedding matrix and an extra dim in the token type embedding matrix for better sharding/partitioning.
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